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An Anthropomimetic Approach to High Performance Traction Control by William Kirchner; Steve C. Southward is a Psychology article available to read on EtoBox.

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## Abstract The ability to learn and adapt to changing environmental conditions, as well as develop perceptive models based on stimulus-response data, provides expert human drivers with significant advantages. When it comes to bandwidth, accuracy, and repeatability, automatic control systems have clear advantages over humans; however, most high performance control systems lack many of the unique abilities of a human expert. This paper documents our first step toward the development of a novel automatic traction control algorithm using an anthropomimetic approach. The primary objective of this approach was to synthesize a high performance longitudinal traction control system by incorporating desirable human behavior distilled from human-in-the-loop (HIL) testing on a 6-DOF driving simulator. The proposed control algorithm was developed in a general framework, and applied to the specific task of longitudinal traction control. Simulation results confirm that the proposed anthropomimetic traction control algorithm provides improved performance relative to a well-tuned conventional PID-based traction control algorithm. Results are also compared with the HIL response data from a behavior

Who reads An Anthropomimetic Approach to High Performance Traction Control?

Author

William Kirchner; Steve C. Southward

Publisher

Walter de Gruyter GmbH

Published

2011

Language

EN

Field

Psychology (Physical Sciences)